Millimeter-scale magnetic rotating swimmers have multiple potential medical applications. They could, for example, navigate inside the bloodstream of a patient toward an occlusion and remove it. Magnetic rotating swimmers have internal magnets and propeller fins with a helical shape. A rotating magnetic field applies torque on the swimmer and makes it rotate. The shape of the swimmer, combined with the rotational movement, generates a propulsive force. Visual feedback is suitable for in-vitro closed-loop control. However, in-vivo procedures will require different feedback modalities due to the opacity of the human body. In this paper, we provide new methods and tools that enable the 3D control of a magnetic swimmer using a 2D ultrasonography device attached to a robotic arm to sense the swimmer’s position. We also provide an algorithm that computes the placement of the robotic arm and a controller that keeps the swimmer within the ultrasound imaging slice. The position measurement and closed-loop control were tested experimentally.

Miniature Magnetic Rotating Swimmers (MMRSs) are untethered machines containing magnetic materials. An external rotating magnetic field produces a torque on the swimmers to make them rotate. MMRSs have propeller fins that convert the rotating motion into forward propulsion. This type of robot has been shown to have potential applications in the medical realm. This paper presents new MMRS designs with (1) an increased permanent magnet volume to increase the available torque and prevent the MMRS from becoming stuck inside a thrombus; (2) new helix designs that produce an increased force to compensate for the weight added by the larger permanent magnet volume; (3) different head drill shape designs that have different interactions with thrombi. The two best MMRS designs were tested experimentally by removing a partially dried 1-hour-old thrombus with flow in a bifurcating artery model. The first MMRS disrupted a large portion of the thrombus. The second MMRS retrieved a small remaining piece of the thrombus. In addition, a tool for inserting, retrieving, and switching MMRSs during an experiment is presented and demonstrated. Finally, this paper shows that the two selected MMRS designs can perform accurate 3D path-following.

This paper presents four data-driven system models for a magnetically controlled swimmer. The models were derived directly from experimental data, and the accuracy of the models was experimentally demonstrated. Our previous study successfully implemented two non-model-based control algorithms for 3D path-following using PID and model reference adaptive controller (MRAC). This paper focuses on system identification using only experimental data and a model-based control strategy. Four system models were derived: (1) a physical estimation model, (2, 3) Sparse Identification of Nonlinear Dynamics (SINDY), linear system and nonlinear system, and (4) multilayer perceptron (MLP). All four system models were implemented as an estimator of a multi-step Kalman filter. The maximum required sensing interval was increased from 180 ms to 420 ms and the respective tracking error decreased from 9 mm to 4.6 mm. Finally, a Model Predictive Controller (MPC) implementing the linear SINDY model was tested for 3D path-following and shown to be computationally efficient and offers performances comparable to other control methods.

For biomedical applications in targeted therapy delivery and interventions, a large swarm of micro-scale particles (“agents”) has to be moved through a maze-like environment (“vascular system”) to a target region (“tumor”). Due to limited on-board capabilities, these agents cannot move autonomously; instead, they are controlled by an external global force that acts uniformly on all particles. In this work, we demonstrate how to use a time-varying magnetic field to gather particles to a desired location. We use reinforcement learning to train networks to efficiently gather particles. Methods to overcome the simulation-to-reality gap are explained, and the trained networks are deployed on a set of mazes and goal locations. The hardware experiments demonstrate fast convergence, and robustness to both sensor and actuation noise. To encourage extensions and to serve as a benchmark for the reinforcement learning community, the code is available at Github.

This work presents an online trajectory generation algorithm using a sinusoidal jerk profile. The generator takes initial acceleration, velocity and position as input, and plans a multi-segment trajectory to a goal position under jerk, acceleration, and velocity limits. By analyzing the critical constraints and conditions, the corresponding closed-form solution for the time factors and trajectory profiles are derived. The proposed algorithm was first derived in Mathematica and then converted into a C++ implementation. Finally, the algorithm was utilized and demonstrated in ROS & Gazebo using a UR3 robot. Both the Mathematica and C++ implementations can be accessed at https://github.com/Haoran-Zhao/Jerk-continuous-online-trajectory-generator-with-constraints.git

Rotating miniature magnetic swimmers are de-vices that could navigate within the bloodstream to access remote locations of the body and perform minimally invasive procedures. The rotational movement could be used, for example, to abrade a pulmonary embolus. Some regions, such as the heart, are challenging to navigate. Cardiac and respiratory motions of the heart combined with a fast and variable blood flow necessitate a highly agile swimmer. This swimmer should minimize contact with the walls of the blood vessels and the cardiac structures to mitigate the risk of complications. This paper presents experimental tests of a millimeter-scale magnetic helical swimmer navigating in a blood-mimicking solution and describes its turning capabilities. The step-out frequency and the position error were measured for different values of turn radius. The paper also introduces rapid movements that increase the swimmer's agility and demonstrates these experimentally on a complex 3D trajectory.

There are many design trade-offs when building a magnetic manipulator to control millimeter-scale rotating magnetic swimmers for surgical applications.For example, increasing the magnitude of the flux density generated by the magnetic manipulator increases the torque applied to the swimmer, which could enable performing a wider variety of surgical tasks in the future. However, producing stronger magnetic fields has drawbacks, such as increased active power usage.To produce a quickly rotating field, EMs must be quickly charged and discharged. This results in a low power factor (high reactive power used in comparison with the active power). Adding capacitors in series with the electromagnets improves the power factor because the capacitors can provide reactive power. With this method, larger flux densities can be produced without necessitating an increase of the apparent power delivered by the power supplies.This paper highlights the benefits of using capacitors for the magnetic manipulation of rotating swimmers. Rotating swimmers can be used to remove blood clots. The clot removal rate of resonating magnetic manipulators is measured using a realistic blood clot model. This paper also presents a control method for the currents inside the electromagnets that enable 3D navigation without current sensing.

This article presents a miniature magnetic swimmer and a control apparatus able to perform both 3-D path following and blood clot removal. The robots are 2.5 mm in diameter, 6 mm in length, contain an internal permanent magnet, and have cutting tips coated in diamond powder. The robots are magnetically propelled by an external magnetic system using three coil pairs arranged orthogonally. A range of robot tip designs were tested for abrading human blood clots in vitro. The best design removed a blood clot at a maximum rate of 20.13 mm3/min. A controller for 3-D navigation is presented and tested. The best prototype was used in an experiment that combined both 3-D path following and blood clot removal.

This paper investigates strategies for 3D multi-agent position control using a shared control input and self-propelled agents. The only control inputs allowed are rotation commands that rotate all agents by the same rotation matrix. In the 2D case, only two degrees-of-freedom (DOF) in position are controllable. We review controllability results in 2D, and then show that interesting things happen in 3D. We provide control laws for steering up to nine DOF in position, which can be mapped in various ways, including to control the x, y, z position of three agents, make four agents meet, or reduce the spread of n agents.

This study investigates the high speed 3D navigation of rotating millimeter-scale swimmers. The swimmers have a spiral-shaped surface to ensure propulsion. The rotational movement is used for propulsion and, in future work, could provide the power needed to remove blood clots. For instance, an abrasive tip could be used to progressively grind a blood clot. An algorithm to perform 3D control of rotating millimeter-scale swimmers was implemented and tested experimentally. The swimmers can follow a trajectory and can navigate without touching the walls inside a tube having a diameter of 15 mm. This diameter is smaller than the average diameter of the distal descending aorta, which is the smallest section of the aorta. Several swimmers designs were built and tested. The maximum velocity recorded for our best swimmer was 103.6 mm/s with a rotational speed of 477.5 rotations per second.

Image-guided and robot-assisted surgical procedures are rapidly evolving due to their potential to improve patient management and cost effectiveness. Magnetic Resonance Imaging (MRI) is used for pre-operative planning and is also investigated for real-time intra-operative guidance. A new type of technology is emerging that uses the magnetic field gradients of the MR scanner to maneuver ferromagnetic agents for local delivery of therapeutics. With this approach, MRI is both a sensor and forms a closed-loop controlled entity that behaves as a robot (we refer to them as MRbots). The objective of this paper is to introduce a computational framework for preoperative planning using MRI and modeling of MRbot maneuvering inside tortuous blood vessels. This platform generates a virtual corridor that represents a safety zone inside the vessel that is then used to access the safety of the MRbot maneuvering. In addition, to improve safety we introduce a control that sets speed based on the local curvature of the vessel. The functionality of the framework was then tested on a realistic operational scenario of accessing a neurological lesion, a meningioma. This virtual case study demonstrated the functionality and potential of MRbots as well as revealed two primary challenges: real-time MRI (during propulsion) and the need of very strong gradients for maneuvering small MRbots inside narrow cerebral vessels. Our ongoing research focuses on further developing the computational core, MR tracking methods, and on-line interfacing to the MR scanner.